Schedule: Full Time

Job Type: Hybrid

Salary Type: Salary

Req #: 2643

About The Role

As a Sr. Systems Engineer on Uber Freight's Platform Engineering team, you'll lead the design and implementation of AI-powered developer experience tools that transform how 150+ engineering, product, and design teams work. You'll combine deep infrastructure expertise with Claude API mastery to architect autonomous workflows, intelligent dashboards, and organization-wide automation that multiplies engineering productivity.

This is technical leadership for internal DevEx. You'll define standards for AI-first tooling, lead cross-functional initiatives, and mentor engineers on building production AI systems. You'll architect solutions that serve the entire CTO organization — not just write code, but establish patterns others follow.

Your working style is AI-first. You default to Claude API and MCP for every automation opportunity. You think in autonomous agents, not scripts. You ship tools that learn and adapt, and you set the technical direction for how the org builds intelligent automation.

What The Candidate Will Do

Architect AI-Powered DevEx Systems

Design and lead implementation of organization-wide DevEx platforms (like Athena: 150K JIRA issues, $35M budget tracking, CTO-wide visibility)
Architect autonomous workflows — multi-agent systems for incident response, code review, deployment validation, and operational toil reduction
Define MCP server standards — establish patterns for exposing internal systems (Vault, JIRA, Datadog, Jenkins) to Claude Code
Lead technical initiatives — drive cross-team projects from requirements through production deployment
Establish AI-first best practices — prompt engineering patterns, agent orchestration frameworks, error handling, observability for AI systems

Drive Organization-Wide Impact

Set technical standards for DevEx tooling across Platform Engineering, SRE, and Data Engineering teams
Lead critical incident response for internal tools — advanced root cause analysis, system-wide reliability improvements
Optimize organization-level systems — architect solutions that improve scalability, efficiency, and developer productivity metrics
Define observability strategy for AI-powered tools — metrics, dashboards, alerts, and runbooks that ensure operational excellence
Establish security and compliance frameworks — audit AI workflows, manage secrets (Vault), enforce RBAC and network policies

Technical Leadership & Mentorship

Mentor engineers on AI integration patterns, MCP server development, and autonomous agent design
Lead code reviews for complex AI systems — ensure quality, maintainability, and adherence to standards
Define and enforce operational best practices — CI/CD patterns, deployment strategies, monitoring standards
Collaborate cross-functionally — work with SRE, DevOps, Data Engineering, Finance, and Product to align tooling with organizational goals
Drive technical innovation — research emerging AI capabilities, prototype new approaches, evangelize successful patterns

Own End-to-End Systems

Architect multi-region, hybrid-cloud solutions for high-availability DevEx tools (GCP primary, OCI, Azure)
Design and implement organization-level CI/CD systems integrated with AI agents for auto-remediation
Lead integration projects spanning multiple teams — JIRA + GitHub + Datadog + Vault + PagerDuty data pipelines
Manage infrastructure at scale — Kubernetes (GKE Autopilot), Terraform/Terragrunt, ConfigSync GitOps
Ensure compliance with security standards, audit requirements, and reliability SLOs

Basic Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
Experience: 8-12 years in platform engineering, DevOps, SRE, or infrastructure roles
Proven AI expertise: Track record of building production systems with LLM APIs (Claude, OpenAI, etc.)
Technical depth: Expert-level Python, Go, or TypeScript — can architect and build complex web applications and distributed systems
Infrastructure mastery: Deep hands-on experience with Kubernetes, Terraform, multi-cloud platforms, and production operations
Leadership: Demonstrated experience leading technical initiatives and mentoring engineers

Preferred Qualifications

AI & Automation Leadership

Claude API mastery — advanced patterns: prompt caching, extended thinking, batch processing, streaming with tool use, multi-agent orchestration
MCP protocol expertise — built production MCP servers or contributed to MCP ecosystem; deep understanding of protocol design
Agent framework design — architected custom agent orchestration systems, not just used off-the-shelf frameworks
Autonomous systems — built self-healing, self-improving AI workflows that operate at production scale
Prompt engineering excellence — published patterns, reusable templates, measurable improvements in AI system performance

DevEx & Platform Leadership

Organization-wide tool adoption — shipped tools used by 50+ engineers; measured and improved adoption metrics
Engineering productivity systems — implemented DORA metrics, JIRA velocity tracking, deployment analytics, or incident management platforms
Observability platform expertise — designed and operated Datadog, Dynatrace, or New Relic at scale; created org-wide monitoring standards
API architecture — designed multi-service API ecosystems with versioning, rate limiting, auth, and comprehensive documentation
Developer experience design — user research, UX for technical tools, onboarding optimization

Infrastructure & Cloud Expertise

Kubernetes at scale — operated production GKE/EKS/AKS clusters serving high-traffic applications (5+ years); expertise in security, networking, autoscaling, disaster recovery
Multi-cloud architecture — designed hybrid solutions spanning GCP, Azure, AWS, or OCI; expertise in Terraform modules and Terragrunt for DRY patterns
GitOps leadership — established ConfigSync, ArgoCD, or Flux patterns for declarative deployments across teams
CI/CD architecture — designed organization-level pipeline frameworks (Jenkins Job DSL, GitHub Actions, Buildkite); integrated AI agents for auto-remediation
Service mesh & traffic management — Istio, Envoy, multi-region routing, BCP/DR strategies

Engineering Excellence & Leadership

Cross-functional leadership — led projects spanning Platform, SRE, Data, Finance teams; aligned technical solutions with business goals
Standards definition — established coding standards, architectural patterns, deployment practices adopted org-wide
Incident management expertise — led critical incident response, performed advanced RCA, implemented system-wide reliability improvements
Security & compliance — managed org-wide security audits, risk assessments, and compliance frameworks (SOC2, ISO27001, etc.)
Technical mentorship — proven track record developing junior/mid-level engineers; created training materials, led workshops

About Uber Freight

Uber Freight helps companies move goods more reliably and efficiently. We bring together the technology, people, and transportation capacity they need, using real‑time data from millions of shipments to guide smarter decisions. That helps customers spot issues early, avoid costly surprises, and deliver on time. Uber Freight works with 1 in 3 Fortune 500 shippers across North America and manages over $17B in freight. Learn more at www.uberfreight.com.

Candidate Privacy Notice

Uber Freight is committed to protecting the privacy of our candidates. We collect and process personal data in accordance with applicable data protection laws. For detailed information on how we handle candidate data, please review our Candidate Privacy Notice.

EEOC

Uber Freight is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regards to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

Sr Systems Engineer

Sr. Systems Engineer